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Titlebook: Discovery Science; 14th International C Tapio Elomaa,Jaakko Hollmén,Heikki Mannila Conference proceedings 2011 Springer-Verlag GmbH Berlin

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51#
發(fā)表于 2025-3-30 10:03:09 | 只看該作者
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發(fā)表于 2025-3-30 14:33:04 | 只看該作者
MEI: Mutual Enhanced Infinite Generative Model for Simultaneous Community and Topic Detection,mber of communities and topics automatically, Hierarchical/Dirichlet Process Mixture model (H/DPM) is employed. Gibbs sampling based approach is adopted to learn the model parameters. Experiments are conducted on the co-author network extracted from DBLP where each author is associated with his/her
53#
發(fā)表于 2025-3-30 17:50:13 | 只看該作者
Detecting Anti-majority Opinionists Using Value-Weighted Mixture Voter Model, the highest value prevails and wins when the opinion values are non-uniform, whereas the opinion share prediction problem becomes ill-defined and any opinion can win when the opinion values are uniform. The simulation results support that this holds for typical real world social networks.
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發(fā)表于 2025-3-31 00:30:49 | 只看該作者
Context-Aware Personal Route Recognition,e this problem we incorporate external contextual information (e.g. time of the day) into route recognition from trajectory. We develop a technique to determine from the historical data how the probability of a route depends on contextual features and adjust (post-correct) the route recognition outp
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發(fā)表于 2025-3-31 01:07:56 | 只看該作者
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發(fā)表于 2025-3-31 10:58:24 | 只看該作者
https://doi.org/10.1007/978-3-642-24477-3autonomous exploration; data mining; kernel methods; social network analysis; user interface; algorithm a
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發(fā)表于 2025-3-31 15:38:15 | 只看該作者
978-3-642-24476-6Springer-Verlag GmbH Berlin Heidelberg 2011
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發(fā)表于 2025-3-31 22:55:47 | 只看該作者
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